Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models

14 January 2015

Papers citing "Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models"

34 / 34 papers shown

Title
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 66 9 0 17 Feb 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 106 0 0 20 Jan 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 108 2 0 17 Jan 2025
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC F. Llorente Luca Martino Jesse Read D. Delgado OffRL 58 13 0 03 Jan 2025
Compositional simulation-based inference for time series Manuel Gloeckler S. Toyota Kenji Fukumizu Jakob H Macke 34 1 0 05 Nov 2024
Full-waveform earthquake source inversion using simulation-based inference A. A. Saoulis Davide Piras A. Spurio Mancini B. Joachimi A. M. G. Ferreira 35 0 0 30 Oct 2024
Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space Tigran Ramazyan M. Hushchyn D. Derkach 16 0 0 16 Jul 2024
Copula Approximate Bayesian Computation Using Distribution Random Forests G. Karabatsos 32 1 0 28 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 16 0 0 30 Jan 2024
Optimal simulation-based Bayesian decisions Justin Alsing Thomas D. P. Edwards Benjamin Dan Wandelt 15 2 0 09 Nov 2023
Learning Hybrid Dynamics Models With Simulator-Informed Latent States K. Ensinger Sebastian Ziesche Sebastian Trimpe 17 1 0 06 Sep 2023
A Bayesian Optimization approach for calibrating large-scale activity-based transport models S. Agriesti Vladimir Kuzmanovski Jaakko Hollmén C. Roncoli Bat-hen Nahmias-Biran 15 5 0 07 Feb 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 36 12 0 27 Jan 2023
Differentiable User Models Alex Hamalainen Mustafa Mert cCelikok Samuel Kaski 17 1 0 29 Nov 2022
Simulation-based inference of Bayesian hierarchical models while checking for model misspecification F. Leclercq 23 6 0 22 Sep 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 19 3 0 04 Aug 2022
Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output J. Corander Ulpu Remes Ida Holopainen T. Koski 20 0 0 22 May 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 12 5 0 07 Jan 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 27 25 0 20 Dec 2021
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 20 31 0 25 Nov 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 15 33 0 12 Feb 2021
Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev Henri Pesonen Markus Heinonen J. Corander Samuel Kaski GP 11 10 0 18 Jun 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods Luigi Acerbi 6 40 0 15 Jun 2020
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 14 64 0 19 Feb 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 31 117 0 10 Feb 2020
Robust Optimisation Monte Carlo Borislav Ikonomov Michael U. Gutmann 9 8 0 01 Apr 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments David T. Frazier David J. Nott Christopher C. Drovandi Robert Kohn 16 40 0 13 Feb 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 18 358 0 18 May 2018
Kernel Recursive ABC: Point Estimation with Intractable Likelihood T. Kajihara Motonobu Kanagawa Keisuke Yamazaki Kenji Fukumizu 21 13 0 23 Feb 2018
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation Ritabrata Dutta Marcel Schoengens Lorenzo Pacchiardi Avinash Ummadisingu Nicole Widmer Pierre Künzli J. Onnela Antonietta Mira 21 25 0 13 Nov 2017
Inverse Reinforcement Learning from Summary Data A. Kangasrääsiö Samuel Kaski OffRL 17 15 0 28 Mar 2017
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 14 412 0 11 Oct 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 17 158 0 20 May 2016
Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model M. Moores Geoff K. Nicholls A. Pettitt Kerrie Mengersen TPM 27 22 0 27 Mar 2015